Current sprinkler systems have their irrigation schedules set manually at the beginning of a watering season and are not adjusted according to the weather. Worse, homeowners typically lack the knowledge about their landscaping or sprinkler system to understand the optimal irrigation schedule. The result is either an over-watered lawn with much water wasted as runoff, an under-watered lawn, or both depending on the sprinkler zone or location with the sprinkler zone.
Additionally, most current sprinkler systems lack the flexibility to handle any type of eccentric irrigation schedule. For example, the typical sprinkler system controller cannot handle more than a couple of irrigation schedules for a zone. And adjusting the schedule both is time consuming and results in shifting from either an under-watered lawn to an over-watered lawn or vice versa.
Current automated sprinkler systems have attempted to bring some efficiency to this process by including sensors that keep track local weather conditions. But, those devices still must be adjusted and require expensive equipment for tracking rain, wind, and humidity. The hardware included in those sprinkler systems can break or malfunction easily because of their exposure. Further, the sensors must be expertly placed to be effective. Even then, those systems can provide only meteorological input into determining any irrigation schedule adjustments and over-watering or under-watering can still result. Sensors can give readings that do not necessarily result in optimal irrigation and this problem is exacerbated when sensors are misplaced, even slightly.
Other automated sprinkler systems take into account historic and predicted weather data to adjust irrigation schedules. Such systems cannot accurately adjust irrigation cycles given that weather forecasts are often wrong or do not accurately reflect weather at the particular site. As a result, these systems can adjust irrigation cycles to the detriment of the landscape health. To compensate, these systems also often rely on sensors and, thus, suffer the same problems described above.
Yet other systems adjust irrigation schedules according to evapotranspiration (ET) information. Again, these systems require the use of sensors susceptible to malfunctioning and expensive controllers to be effective and, again, suffer the same as the systems described above. One example of one automated sprinkler system is described in U.S. Pat. No. 5,870,302 (“Oliver”). In particular, Oliver and similar systems use ET and predicted precipitation data to control an irrigation system. Although these systems address problems associated with depleted moisture levels by detecting moisture levels directly or using other, external data to guess whether moisture levels are depleted and then adjusting an irrigation schedule, they are still closed loop systems that adjust irrigation schedules based solely on empirical sensor data, or systems reliant on historical or forecast weather data.
In the former type of system, they obtain empirical information but require the same costly equipment to obtain it. Moreover, the empirical information they gather cannot truly indicate landscape health. The latter type of system can be implemented more cheaply, both in the long and the short term, but it lacks empirical information and, as a result, can be no more successful at gauging optimal irrigation cycle times and schedules.
Oliver in particular discusses basing an ET value on baseline conditions and then adjusting the irrigation schedules based on predicted and historical weather data. However, here Oliver lacks any ability to determine whether the baseline ET value was correct or continues to provide an accurate baseline. In particular, Oliver bases the ET value only on geographical information and objective data. Thus, Oliver is useful only to the extent a baseline irrigation schedule or ET value is correct and that an adjusted ET value is calculated properly and accurately reflects the landscape. Even then, unless the system employs sensor equipment the actual ET values that Oliver uses to determine when to run a watering cycle, Oliver has only forecasted and historic weather data to rely on. That weather data alone, obtained from a weather service, not sensor equipment at the site, cannot reliably indicate actual precipitation, wind, humidity, etc. at a particular site. As a result, under-watering or over-watering can still be an ongoing concern. Indeed, Oliver and other similar systems can run an irrigation cycle during a precipitation event where a weather forecast is inaccurate. Although Oliver and other similar systems can achieve savings in the short term, they cannot provide long-term flexibility as the irrigated landscape changes over time. Moreover, in many cases, they savings fall short where predicted weather is inaccurate, where sensor data is flawed, or where sensors fail. In the end, Oliver either requires the same costly and wear-prone equipment of a closed loop system or suffers similar problems that conventional sprinkler systems suffer.
Although present devices are functional, they are not sufficiently functional or otherwise satisfactory. Accordingly, a system and method are needed to address the shortfalls of present technology and to provide other new and innovative features.